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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 15 Dec 2010 17:50:43 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/15/t1292435422l8ntucwmf3o0w3s.htm/, Retrieved Fri, 03 May 2024 04:26:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110622, Retrieved Fri, 03 May 2024 04:26:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPaper DMA
Estimated Impact136

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [Ws4 part 1.1 s090...] [2009-10-27 21:56:53] [e0fc65a5811681d807296d590d5b45de]
-  M D    [Bivariate Explorative Data Analysis] [Paper; bivariate ...] [2009-12-19 19:10:37] [e0fc65a5811681d807296d590d5b45de]
- RMPD      [Cross Correlation Function] [cross correlation...] [2010-12-08 19:50:23] [74be16979710d4c4e7c6647856088456]
-   PD        [Cross Correlation Function] [] [2010-12-09 09:25:48] [b98453cac15ba1066b407e146608df68]
- R P           [Cross Correlation Function] [PAPER DMA Cross C...] [2010-12-09 19:56:08] [2099aacba481f75a7f949aa310cab952]
-   P               [Cross Correlation Function] [Paper DMA Cross C...] [2010-12-15 17:50:43] [f92ba2b01007f169e2985fcc57236bd0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3030.29
2803.47
2767.63
2882.6
2863.36
2897.06
3012.61
3142.95
3032.93
3045.78
3110.52
3013.24
2987.1
2995.55
2833.18
2848.96
2794.83
2845.26
2915.03
2892.63
2604.42
2641.65
2659.81
2638.53
2720.25
2745.88
2735.7
2811.7
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042
1995.37
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2093.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
Dataseries Y:
Download CSV
Histogram 
25.64
27.97
27.62
23.31
29.07
29.58
28.63
29.92
32.68
31.54
32.43
26.54
25.85
27.6
25.71
25.38
28.57
27.64
25.36
25.9
26.29
21.74
19.2
19.32
19.82
20.36
24.31
25.97
25.61
24.67
25.59
26.09
28.37
27.34
24.46
27.46
30.23
32.33
29.87
24.87
25.48
27.28
28.24
29.58
26.95
29.08
28.76
29.59
30.7
30.52
32.67
33.19
37.13
35.54
37.75
41.84
42.94
49.14
44.61
40.22
44.23
45.85
53.38
53.26
51.8
55.3
57.81
63.96
63.77
59.15
56.12
57.42
63.52
61.71
63.01
68.18
72.03
69.75
74.41
74.33
64.24
60.03
59.44
62.5
55.04
58.34
61.92
67.65
67.68
70.3
75.26
71.44
76.36
81.71
92.6
90.6
92.23
94.09
102.79
109.65
124.05
132.69
135.81
116.07
101.42
75.73
55.48
43.8
45.29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110622&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110622&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110622&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-170.0257852845999390
-160.091394327199122
-150.106961969849184
-140.169311873420538
-130.133401141938320
-120.0912338916692098
-110.107059967996525
-100.0770012165469526
-90.216103761012581
-80.0443208094653134
-70.0749417381583825
-60.0359283264411647
-50.131316867328351
-40.123828761759968
-30.127738582617122
-20.256034045865606
-10.363011396289590
00.211650722570431
10.102002913480296
20.0941893884380982
3-0.0658462938070174
4-0.206728440190675
5-0.114075682489744
6-0.047140699561343
7-0.111829198641799
8-0.0834876532173073
9-0.00516600897285147
100.0175669907347008
11-0.0373762310813965
12-0.0473066457489136
13-0.0554631386010157
140.0560463355008397
15-0.0910217150177488
160.00799701186600794
170.0778878478510805

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \tabularnewline
Seasonal Period (s) & 1 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-17 & 0.0257852845999390 \tabularnewline
-16 & 0.091394327199122 \tabularnewline
-15 & 0.106961969849184 \tabularnewline
-14 & 0.169311873420538 \tabularnewline
-13 & 0.133401141938320 \tabularnewline
-12 & 0.0912338916692098 \tabularnewline
-11 & 0.107059967996525 \tabularnewline
-10 & 0.0770012165469526 \tabularnewline
-9 & 0.216103761012581 \tabularnewline
-8 & 0.0443208094653134 \tabularnewline
-7 & 0.0749417381583825 \tabularnewline
-6 & 0.0359283264411647 \tabularnewline
-5 & 0.131316867328351 \tabularnewline
-4 & 0.123828761759968 \tabularnewline
-3 & 0.127738582617122 \tabularnewline
-2 & 0.256034045865606 \tabularnewline
-1 & 0.363011396289590 \tabularnewline
0 & 0.211650722570431 \tabularnewline
1 & 0.102002913480296 \tabularnewline
2 & 0.0941893884380982 \tabularnewline
3 & -0.0658462938070174 \tabularnewline
4 & -0.206728440190675 \tabularnewline
5 & -0.114075682489744 \tabularnewline
6 & -0.047140699561343 \tabularnewline
7 & -0.111829198641799 \tabularnewline
8 & -0.0834876532173073 \tabularnewline
9 & -0.00516600897285147 \tabularnewline
10 & 0.0175669907347008 \tabularnewline
11 & -0.0373762310813965 \tabularnewline
12 & -0.0473066457489136 \tabularnewline
13 & -0.0554631386010157 \tabularnewline
14 & 0.0560463355008397 \tabularnewline
15 & -0.0910217150177488 \tabularnewline
16 & 0.00799701186600794 \tabularnewline
17 & 0.0778878478510805 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110622&T=1

[TABLE]
[ROW][C]Cross Correlation Function[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of X series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]1[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-17[/C][C]0.0257852845999390[/C][/ROW]
[ROW][C]-16[/C][C]0.091394327199122[/C][/ROW]
[ROW][C]-15[/C][C]0.106961969849184[/C][/ROW]
[ROW][C]-14[/C][C]0.169311873420538[/C][/ROW]
[ROW][C]-13[/C][C]0.133401141938320[/C][/ROW]
[ROW][C]-12[/C][C]0.0912338916692098[/C][/ROW]
[ROW][C]-11[/C][C]0.107059967996525[/C][/ROW]
[ROW][C]-10[/C][C]0.0770012165469526[/C][/ROW]
[ROW][C]-9[/C][C]0.216103761012581[/C][/ROW]
[ROW][C]-8[/C][C]0.0443208094653134[/C][/ROW]
[ROW][C]-7[/C][C]0.0749417381583825[/C][/ROW]
[ROW][C]-6[/C][C]0.0359283264411647[/C][/ROW]
[ROW][C]-5[/C][C]0.131316867328351[/C][/ROW]
[ROW][C]-4[/C][C]0.123828761759968[/C][/ROW]
[ROW][C]-3[/C][C]0.127738582617122[/C][/ROW]
[ROW][C]-2[/C][C]0.256034045865606[/C][/ROW]
[ROW][C]-1[/C][C]0.363011396289590[/C][/ROW]
[ROW][C]0[/C][C]0.211650722570431[/C][/ROW]
[ROW][C]1[/C][C]0.102002913480296[/C][/ROW]
[ROW][C]2[/C][C]0.0941893884380982[/C][/ROW]
[ROW][C]3[/C][C]-0.0658462938070174[/C][/ROW]
[ROW][C]4[/C][C]-0.206728440190675[/C][/ROW]
[ROW][C]5[/C][C]-0.114075682489744[/C][/ROW]
[ROW][C]6[/C][C]-0.047140699561343[/C][/ROW]
[ROW][C]7[/C][C]-0.111829198641799[/C][/ROW]
[ROW][C]8[/C][C]-0.0834876532173073[/C][/ROW]
[ROW][C]9[/C][C]-0.00516600897285147[/C][/ROW]
[ROW][C]10[/C][C]0.0175669907347008[/C][/ROW]
[ROW][C]11[/C][C]-0.0373762310813965[/C][/ROW]
[ROW][C]12[/C][C]-0.0473066457489136[/C][/ROW]
[ROW][C]13[/C][C]-0.0554631386010157[/C][/ROW]
[ROW][C]14[/C][C]0.0560463355008397[/C][/ROW]
[ROW][C]15[/C][C]-0.0910217150177488[/C][/ROW]
[ROW][C]16[/C][C]0.00799701186600794[/C][/ROW]
[ROW][C]17[/C][C]0.0778878478510805[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110622&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110622&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-170.0257852845999390
-160.091394327199122
-150.106961969849184
-140.169311873420538
-130.133401141938320
-120.0912338916692098
-110.107059967996525
-100.0770012165469526
-90.216103761012581
-80.0443208094653134
-70.0749417381583825
-60.0359283264411647
-50.131316867328351
-40.123828761759968
-30.127738582617122
-20.256034045865606
-10.363011396289590
00.211650722570431
10.102002913480296
20.0941893884380982
3-0.0658462938070174
4-0.206728440190675
5-0.114075682489744
6-0.047140699561343
7-0.111829198641799
8-0.0834876532173073
9-0.00516600897285147
100.0175669907347008
11-0.0373762310813965
12-0.0473066457489136
13-0.0554631386010157
140.0560463355008397
15-0.0910217150177488
160.00799701186600794
170.0778878478510805


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 1 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 1 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par5 == 0) {
y <- log(y)
} else {
y <- (y ^ par5 - 1) / par5
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par6 > 0) y <- diff(y,lag=1,difference=par6)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
if (par7 > 0) y <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',ylab='CCF',xlab='Lag (k)'))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Cross Correlation Function',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of X series',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of X series',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of X series',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of Y series',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of Y series',header=TRUE)
a<-table.element(a,par6)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of Y series',header=TRUE)
a<-table.element(a,par7)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'k',header=TRUE)
a<-table.element(a,'rho(Y[t],X[t+k])',header=TRUE)
a<-table.row.end(a)
mylength <- length(r$acf)
myhalf <- floor((mylength-1)/2)
for (i in 1:mylength) {
a<-table.row.start(a)
a<-table.element(a,i-myhalf-1,header=TRUE)
a<-table.element(a,r$acf[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')